Various techniques are currently being utilized to understand written human language, such as natural language processing. Natural language processing is a field of computer science, artificial intelligence and computation linguistics concerned with the interactions between computers and human (natural) languages. As such, natural language processing involves natural language understanding enabling computers to derive meaning from human or natural language input.
However, understanding written human language across various linguistic domains is an increasing challenge. A “linguistic domain,” as used herein, refers to a sphere of knowledge. For example, an ambiguous phrase may have different meanings based on the context of the use of the phrase. For instance, a natural language processing system may understand terms used in the linguistic domain of animals, but when the system is expanded to process terms used in the linguistic domain of car brands, the natural language processing system may not be able to distinguish the term “Pinto” from referring to a horse or a car.
Disambiguating the meaning of terms with multiple meanings is important in various areas, including business and academic applications. For example, in the context of a business application used for drug safety, it is important to distinguish between when a mentioned concept refers to a risk as opposed to a precondition. The inability to make clear distinctions can degrade efficiency in the process of obtaining approval to market a drug by the U.S. Food and Drug Administration as well as increase cost by requiring human involvement.
In another example where it is important to disambiguate the meaning of terms by attributing the correct meaning to the term in question (accurately assigning the role to the term), accurate role assignment is important in social media extraction. For example, knowing the sense of a noun is important to track the sentiment. For instance, if a social media post uses the term “BP,” the term “BP” may refer to the oil and gas company British Petroleum or to a birthday party. In order to correctly track sentiment, it is important to attribute the correct meaning to the term.
By disambiguating the meaning of terms with multiple meanings, the utilization of applications, such as business and academic applications, is improved by reducing misclassification and increasing the confidence in decision making.
Unfortunately, there is not currently a language independent example drive means for effectively disambiguating the meaning of terms with multiple meanings.